Hiten Patel: Thank you very much for joining us on today's episode of the Innovators’ Exchange, and I'm delighted to be joined by Tara Anand Carter from Hg, where she is a Partner. Welcome to the show, Tara.
Tara Carter: Thank you for having me, pleasure to be here.
Hiten: It'd be great just to kick things off by hearing from you about your role at your current company.
Tara: Absolutely. As you said, I'm a partner at Hg, and Hg is a private equity firm. We focus exclusively on investing in European and transatlantic B2B software and services businesses. The firm was founded as an independent one in 2000. Today we're close to 400 people in London, Munich, Paris, New York, and San Francisco. We have approximately 50 portfolio companies and the aggregate enterprise value of those is north of 150 billion dollars. So that makes us, together with them, one of the largest European software and tech firms. We have 3 different fund strategies, but all with the same sector focus that allow us to partner with companies large and small. And I'm a partner in our Genesis fund. It's our mid-market fund, where we typically write checks of 400 to a billion euros.
Hiten: Awesome, awesome. And you've recently joined, right? I'm really interested in your career arc, you know, starting life out at a bulge bracket bank, and then a boutique bank. I always love to hear about people's journeys, and I think yours is a particularly compelling one, so it'd be great to kind of rewind the tape and hear about things from the start.
Tara: Absolutely. As you say, I joined Hg in early 2024, although I'd known the firm for many years, after a 20-year career in investment banking. If we go way back, I interned at what was then Schroder Salomon Smith Barney in the summer between my penultimate and final year at university and when I graduated, I joined what was then Citigroup in the telecom, media, technology investment banking team on the analyst program. I spent 5 years there, probably working harder and surviving on less sleep than I knew was physically possible, and it was incredible, but very intense. And I found myself predominantly working with American MDs on transatlantic transactions, so I routinely got sent to the US. And this was everything from global TV production and distribution, regional UK newspapers and radio stations, Serbian mobile phone operators and, cruise companies. It was a wild time, because it was also a time of physical data rooms, hanging around till ungodly hours of the night, delivering books to people at like 6 in the morning and getting told off if you woke up their kids when they went through the letterbox. It was insane if you think of the lifestyle looking back. But I learned a huge amount and it was an incredible foundation.
Tara: Obviously, for me, I decided that wasn't a particularly sustainable way of life, and I wanted to specialize more. I'd worked out that I really enjoyed the media and tech piece of what we were doing. And after a few months of thinking about it, I was actually asked by a former mentor to do a short stint at a boutique advisor called Quayle Munro, and the intention was to do just a few months' work, help them execute some sell sides in the, sort of, what they call media, but was really B2B publishing sector. But in very short order, I think, a matter of days, a permanent contract appeared on my desk, and the next 15 years was written in the stars from there. So, at Quayle Munro we were really in the right place at the right time. One of the predecessor firms, van Tulleken, had a very long and storied history advising B2B publishing companies. And when I joined in 2009, many of these publishers had been on a journey or were on a journey from news and insights to “must-have” data and analytics. I think there was a newfound appreciation for the value of these data sets, and a big customer base, particularly for commodities, financial information and governance, risk and compliance, which is where we ended up specializing. I spent 15 years in variations of that team, including post an acquisition by Houlihan Lokey, where we advised countless companies in the sector.
Tara: And somewhere along the way, I'm not really sure where, I totally fell in love with them and the power of the data and the platforms. I'd advised Hg on many occasions, including the taking private of Ideagen in 2022, and on quite a lot of work in and around the GRC [Governance, Risk, and Compliance] Sector, and Hg participated, or in some case chose not to participate in a number of the sell sides I was working on. And to set the scene, my focus has always been on that mission-critical data and analytics, so used by well-funded end markets to make high value decisions like capital deployment, investment, trading, risk and compliance.
Tara: And my thesis was, and still is, that the businesses have the same characteristics that Hg love to invest behind, so strong IP, recurring revenue, you know, creating a strong and stable foundation for growth. Hg had some success in this subsector, Argus, FE fundinfo, Norstella, and our recent investment in Cube. But we all agreed that we probably should and could do more. Hg values focus and specialization. So that kind of inch wide mile deep knowledge that I was used to really fit quite well. And so, when the opportunity arose to join the team, lead our investment efforts in the sector, you know, put my money where my mouth is, so to speak, it was too good of an opportunity to turn down. And I think, probably for 3 reasons. One, I'm a real geek about this sector, like I love these businesses. I love spending time with the entrepreneurs, with the companies, it really makes me tick. So being able to sort of put my knowledge and network of the last 15 years, and investing rather than advising seemed a pretty natural progression. Secondly, the opportunity of doing it at a firm with the calibre of Hg, working alongside some incredibly talented people was pretty irresistible. But lastly, it's a bit like our Quayle Munro journey, being in the right place at the right time, right? I'd had a great career in banking. I didn't feel like I had a huge amount to prove, and so the opportunity to do something new in my forties, to continue to learn, to develop, it's a real privilege.
Hiten: That's awesome. I mean, I think it just highlights the continuity of that thread. Right? I think it's quite powerful to go all the way back to 2009, right? I think this is a trend that more and more people have been jumping on the bandwagon more recently. But I'd love to get your perspective again around what’s different about this most recent era of investor interest? You're someone who's probably had one of the longest kind of threads of thinking about this. You know multi-decade view, that whole publishing into data businesses, people getting more interest in the value of data assets. In your mind, like, characterize some of the different chapters of that journey and where do you think we are now?
Tara: As you say, it is a pretty interesting one, and I think in the late 2000s, early 2010s a lot of the transactions we were advising on were strategic exits to the like of S&P, IHS, Relx, Thomson Reuters. And what was happening is they worked out they could drive growth and value from niche data sets which plugged product, capability, geographic or customer gaps that they had, and they already had the routes to market. So, they knew how to monetize these data sets. And if you think back to that time, private equity, there were far fewer specialized firms, and even fewer who kind of got these businesses or understood the valuations, because even in those days we were selling businesses in the sort of mid to high single digit revenue multiple.
Tara: And I think over that time the investor universe sort of in the last 15 years, particularly the first ten, the universe involved from an invest standpoint, things like the Wood Mackenzie journey that was backed by multiple different private equity backers, and a few other stories really helped private equity understand the enduring value of these platforms. But I also think that management teams and founders became more sophisticated and more confident of what they could do outside the confines of a large strategic. I think they used to think they needed that route to market to be able to get value out of what they've created. And I think that's changed. Partly, there's been a huge amount of innovation in the data and analytics, sort of, in what people are able to deliver, how and why, and how to get it to people in a pretty streamlined fashion. There have been new markets, new asset classes where no one had the routes to market. So actually, it was totally possible to come and build some of those routes to market, and also, the customers are increasingly sophisticated now. They're the ultimate buyers of these solutions, and I think they value that if someone has something that really moves the needle, drives ROI for them, they're much more open minded to try it and see if it works.
Hiten: Yeah, that's really helpful, really helpful framing. Because from where we sit there's this either, can't put my finger on it quite, whether it's intentional or unintentional blurring of this boundary between technology, software and data. And I think increasingly, as you're saying at Hg, seeing investors bridge across that gap, but they don't quite have the lineage and heritage in the data space like they do in the software space. Right? There are a dime a dozen people who say they've invested in software businesses for decades. Just given that you're helping play that role across the transition, what are some of the similarities and differences that people need to understand when they're trying to straddle that boundary between data and technology?
Tara: If we back up to this first part of your question, my personal view is, it's kind of one long continuum from data to software. If you start with the mission critical data businesses at one end, these companies often use analytics and tools. And what they're really doing is embedding those data sets into customers' daily workflows. And often those workflows plug in to some sort of software system of record. So, to me, I think it’s very blurry, although others might disagree or think it’s more black and white. So if we use a worked example, why don't we think about commodities? In commodities land you have a price benchmark businesses, a data business like an Argus, a Platts, a FastMarkets. These companies are publishing the price by which physical and derivative contracts are priced or benchmarked. For example, in oil, gas, metals.
Tara: On top of publishing those prices, what these data companies are actually doing are providing APIs, they are providing scenario modeling tools or forecasts. Any products, any way of helping a market participant understand the sort of the “so what?”. And really get value and drive usage from the data. So, making that data really sticky across lots of different parts of an organization. But when all's said and done, in commodities a customer's taken the market position, and these positions and the risk reward associated with them have to be logged in a system of record, so vertically-specific ERP system, for example. And this platform is there to act as a single source of truth for all of those activities.
Tara: Where Hg have been historically very strong is that we have an incredible track record in investing in vertically-specific ERP businesses, the ones I’ve described on one end, and therefore, for us it has been a natural evolution, you might call it a widening of the aperture to continue to invest along this continuum. We’ve already done some of that and we’d really like to do more. And why? What’s similar? There is a lot that’s similar about these businesses. The businesses we focus on across that continuum have a strong IP, they have a deep moat, usually around a vertical niche. They're predominantly subscription revenue. And they are must-have or mission critical. So their customers are loyal, meaning GRRs [Gross Retention Rate] are northern of 90%, and NRRs [Net Retention Rate] often north of 110%. They are highly predictable, and stable cash flow profiles, and the margins can be anywhere between 35% up to 50%. So, what's different? I guess a key difference for me is that the best data businesses often have recurring or non-recurring revenue streams attached to them. So maybe 20, 25% of the business is not pure subscription revenue. It might be events space, it might be consulting, it might be project-led. And that's really important. It’s important because it really helps you understand what questions your customers are grappling with. If you use them well, these revenue streams are a key driver for product development, of customer lead generation, but also brand awareness, thought leadership, market credibility.
Tara: The other thing that could be quite different to some of the software markets, is that, it’s often a multi-source market. Whereas, you won’t often intentionally have two systems of record software platforms, it's very often actually that customers will buy two or more data and analytics solutions. So, you can have a great business, even if they are the number 2 or number 3 player in a market. And I think we touched on GRRs before. A GRR, might be in the 80s for these businesses on an aggregate basis. You’d expect the core products to have 90%+ GRRs, but actually emerging products that you are developing, where you are trying to establish your product market fit, they might be softer, those GRRs. So, I think we are personally splitting hairs to find the difference.
Hiten: Yeah. And just to spell it out for listeners. There, just GRR, you talk about retention rates, right? Just from an investor perspective. It's just worth you just spelling out some of the key metrics there, you're thinking about retention, both from the software and the data side.
Tara: So, the gross retention rate is the amount of like for like businesses you retain from a customer one year to the next. And you can argue it’s the most pessimistic view of how much value you are retaining from these customers. So, if we start with an aggregate value of the customer base last year, we then deduct any cancellations, known as churns. The cancellation of a whole contract, cancellations of specific products, and we also deduct any down sells, so reduction in a number of seats or modules. And that gives us the gross retention rate. The net retention rate then gives me credit for any expansion revenues from that customer base. So, if they were upsells and if I sold them more seats, or if I increased the prices of those products, and if I cross-sold them products, so additional or new modules products. Easiest way to think about it may be in numbers. If the book of business I had last year was a $100 million, and in aggregate those customers churned or down sold $7 million, my gross retention rate is 93%. However, if those same customers, not counting new customers, paid me an additional $20 million for more licenses, modules, price increases, or products, then my net retention rate is 113%, it’s the 93% plus the $20 million of additional expansion revenue.
Hiten: But ultimately a key metric that you use both on the technology software side as well as the data side, when you're looking at these things.
Tara: Absolutely, because effectively, it tells you on January 1st how much revenue you expect to get that year, that is just a follow on from last year, so really helpful to understand sort of what your base revenue streams are, and therefore cash flows.
Hiten: Just going back to a comment you made earlier in that reply about some of the different components of the revenue stream, so whether that be events or the one-offs, it's always been a fascinating debate or challenge I've had whenever we speak to investors in this space. There's obviously this desire for purity of having everything beautifully recurring and having the best recurring rate, so that as much as the book rolls over on January 1st. And we've often found that it is sometimes challenging for providers in the space to fully articulate their value to investors around the things like events, right? Which are kind of one-off, they're a bit analog, they're a bit in the physical world, but, as you say, can be pretty powerful beacons to show the brand strength of the network. But I mean, how do you navigate some of those challenges internally when you're debating with your colleagues, you’re sat on the investment committee. There's obviously kind of a rigid investor lens that kind of wants to look at some of the beauty of economics. But then, as you say, as you've been almost a practitioner in this space. You've spent time around some of these businesses, and you can understand some of those intangibles. How do you bring people along the journey as they, you know, you try and get a more holistic sense of what the value potential could be around some of these businesses?
Tara: So, I think we do have the benefit of history, of understanding how the market evolved. And that's really important. I think we think about it sort of across the gamut of everything we invest in. When I started, we used to think sort of 5%-10% of non-recurring revenue was the quantum that the big strategics would stomach. They understood the value, but they really didn't want to get too far over that. And I would say over time that has got closer to 25%. It's probably 15%, if you ask them, in their preference. So again, just setting the scene. Even the strategics have come to understand that, it’s a really important piece of the puzzle. And there's a couple of different ways to look at it.
Tara: One is that reoccurring element. A lot of businesses have a fairly consultative sale, and therefore, as they're trying to understand what customers’ pain points are, if they're trying to build relationships, they might start with consulting type projects or one-off type projects. But actually, what you can do in many cases is dig back through and say, well, actually, they spent this revenue with us, maybe not every year, but 2 years out of 3, 3 years out of 4. And, you know, they are what's really you've done with those projects is embed them into the workflows. Right? It's just you haven't necessarily monetized them in a subscription format.
Tara: I think the events, a nice way to do it, I know Charlie Kerr was on your podcast series at some point, you know, Charlie had worked out with their events business how to get proprietary data through the events business, right? A paid, sort of, pay to play in that if you wanted to come to the event, you must give us some extra data sets that he didn't have before. There's lots of different ways to skin a cat, and I think the other way to think about it is, can you prove that through the event series, through the one-off revenue streams that you've created new products.
Tara: Or can you prove that you actually created a club? Right? There are some businesses, for example in the power sector. They got market credibility by creating these little clubs in each specific market they went into, where they invited the brightest and best in that market to come and challenge them, and tell them why they were wrong, and really build a great relationship. So, you're sort of part of the fabric of the industry, harder to prove and that's one of those ones where you really need to understand how these businesses have been around and evolved to probably take people on that journey with you, but lots of different levers that aren't black and white that you could use to try to explain to people what's really going on here.
Hiten: Yeah, hearing you describe that, the words that ring in my head are like context matters, and your ability to be able to kind of put those businesses into the wider context in which they operate and derive value. Just taking a step back, I want to play a little bit more on this unique angle that you've got from being advisor to investor. Talk to us a little bit about what you learned as an advisor that's helping you be an effective investor? Where are those big areas of overlap? Where are the big differences? Not just for the benefit of the audience, but selfishly myself, I've been stuck on the advisor side now for coming up to 2 decades. I'd be keen just to hear as someone who's gone through that transition, what are the reflections?
Tara: Let's caveat this entire response with, I'm pretty early into my investor journey. You know, we've got some great traction and ideas, but I have a lot to learn and execute on before I'd say I'm an effective investor. But setting that to one side, I have had a vantage point of this ecosystem. So, I'm going to give you those perspectives. In my view, the best advisors that I know, know their domain inside out. They know the technical aspects, but equally they know the stakeholders, the behaviors, preferences, red flags. They understand the history, the evolution of the market, why things are the way they are, and therefore how they may or may not evolve in the future. And those advisors, the best advisors can really very quickly get under the skin of a business, right? Understand the core IP, the company, its culture, isolate the key risks, the key calls, and find proof points, or construct solutions to mitigate the risks. And then ultimately, they curate a process to find the right home and to show people all the value inside of a business and help them be able to articulate to their own investment committees or decision-making trees.
Tara: I think the same is absolutely true of the best investors, right? They're very similar muscles you need to use, but the vantage point and the time horizon is just slightly different. So, we have a pretty long-time horizon. We've got some businesses that we have backed for decades. We look for long term compounders. So, the most obvious difference to me as an investor, you've got to live with the consequences, right, for the next five, seven years or longer.
Tara: You've got to help management teams not just big picture strategy, but actually the day to day, like you don't really know what's coming, and you could have the best plan. You could sit there and say we've got 20 great ideas, but a management team can't execute on that. You've got to help them pick three that are really important, to give them the rest of the time to run the actual business day to day. And the reality is you'll never know if you're an effective investor until actually, you've found the next home for that business, and you've delivered returns to your own clients. So, it's a much longer time horizon.
Hiten: Yeah, yeah, no. That's a nice way of framing things. We spent a bit of time looking at the history, and where we've come from. I guess, as you look forward and kind of, you know, what are the next areas and the value creation opportunities for data are? Like, what are some of the end markets and areas that kind of excite you the most.
Tara: I have a long record and affinity with energy and commodities, data and analytics. And that spans from oil, gas, power, energy transition, agri-food commodities, freight maritime and financial markets and regulatory compliance. My view, and I think our view as a house, is these sectors will continue to evolve. They're enormous. And there's lots of participants who are impacted by changes. I think the one thing I probably haven't mentioned that's fundamental to this sector is that volatility is good for business. Volatility and change in a market or sector, be it pricing, landscape, asset allocation, risk, regulatory burden, that drives the need for timely and accurate data. It also drives adoption. It drives stickiness. So, these might be established markets. But there's so much still going on there, and the decisions that people are making are multi-million, sometimes multi-billion-dollar decisions, which means they are happy and have the resources to pay for anything that helps them make better decisions. So, you know, they're not new sectors, but they are sectors that I know and love for a reason and have been around a long time for a reason.
Hiten: And one of the questions that's on my mind is like, how far could things evolve in that energy commodities sector in particular? If I look at the world, historically it’s been quite obsessed with financial data, right? If you look at, you know, the size of the market, the revenue pools, the big companies that have borne out and feels now like we're on another wave of quite a step change in growth and importance of things like the energy, the commodities you mentioned, and the climate transition. But I, what we sometimes wrestle with is, how far do you think that goes? And I don't know if you've got views on kind of, you know, when you fast forward the tape five, ten years, what would the space in that area look like?
Tara: I think there's so much [to go]. If you think of the energy transition and all of the macro trends around that, the reality is this market is not going to become stable anytime soon. So, noting “volatility is good” or “change is good”, then, I think, you could have a pretty safe bet that demand requirements are going to continue to increase. As is the pressure to be more sustainable, as is the technology, you know, with new technological advancements, the participants who enter into a market [changes]. There's lots of different things going on there that change the makeup of these markets and, therefore, who cares about them and why- they'll come from different vantage points, different backgrounds. If you are investors in a data center you're really going to care about power, right? Because what does a data center need? It needs a huge amount of power for the compute, but it also needs a huge amount of power for cooling systems. So I think, some of those people will think differently. Some of those are more sophisticated from a tech perspective and therefore will want to ingest data, consume data, insights, analytics in a slightly different way. So I think, understanding who's interested in these markets and why, and what is the problem they're solving for.
Tara: If you think some of the best businesses we've seen lately, or some of the super high growth, something like a Kpler…they sat there and they said, “well, there's a problem here that the traders are trying to piece together lots of different data sets. Some they might know, some they might not know, they might guess. How do we create a solution that actually just gives them insights that aren't readily available to them today?” I think we will continue to see lots of different ways that people will address challenges because the challenges and the questions that people need to answer will continue to change.
Hiten: I know, hearing you talk, it's, I was about to say I wasn't around in the eighties, but I was around, but not old enough to care about this part of the market, but I imagine someone sat there in the eighties looking about what was about to happen in financial services and the role and the value that data was going to play. You could probably think if you sat here now, we're about to go through that change in, as you say, anything related to the energy transition, climate transition and that space. You say just the number of decisions that need to be made. The value of those decisions, the complexity of piecing it together. So always conscious not to overhype it but it does feel like there's a coming-of-age element around some of these components that might ultimately deliver quite a step change in the importance of this market.
Tara: Oh, I agree. And again, same, if you think about the other areas I mentioned, so financial markets, they will continue to evolve risk and regulation, right. The burden of regulation is a one-way bet. And again I remember in the advent of my banking career, the Quayle Munro days, risk had gone from a just “tick the box” exercise to, over time, a C-suite problem, where the implications of getting it wrong, and the burden of responsibility had been pushed right back onto the corporates. And therefore, that impacted budgets, it impacted decision making, it impacted need for someone to help them get it right. So I don't think that's changing. The reality is it is different types of regulation. Maybe it's operational compliance and product compliance. You know, it could be all sorts of different things. But I agree, there's still, I think there's a long way left to go in these markets.
Hiten: Very nicely put. I've been holding off as long as I could without mentioning AI. But at any conversation that involves data we have to get to it. But give us your thoughts, right. What does AI have to do with this space? Has the hype been too much? Has the impact being oversold? Does it just need more time like, where do you sit on this debate?
Tara: So, like you, I don't think a day goes by around here when we don't talk about AI or think about AI, but actually, what we're really talking about is generative AI, right? Most of the companies in our ecosystem have been using variations of machine learning and AI for a number of years. And there's a few ways to think about it. So let me think about it in 3 horizons. The first one, using generative AI to deliver tangible cost efficiencies, so for example R&D teams leveraging AI to help coders code faster, help customer support reps deal with tickets more efficiently. That's pretty easy to understand and across the portfolio we're already seeing sort of 15%, 20% efficiency gains in terms of automating or speeding up existing workflows. If you think about data businesses specifically, they spend a vast amount of resource and capital collating, curating and interpreting the data. So again, you've got to think there are efficiency savings to be made there that are quite low hanging fruit, given where we are now, with the availability and cost effectiveness of using some of these tools.
Tara: But the one caveat I'd have in data-land is quality is key. It's really important to implement AI thoughtfully, and without losing sight of what the customers are buying the data analytics for, and why? What do they value? So, I think that's an easy piece to understand. I think the next piece of the generative AI journey is top line. New features, new products that increase revenue, make things stickier. And this is a really exciting piece, I think, particularly for data businesses, because I recall for many years listening to companies in the space talking about creating unified data lakes, right? And every M&A deal we ever did was all about ‘Oh, God! How are we going to get this into a data lake? What are we doing here?’ And it was all about how do you get data sets to talk to each other so that you can interrogate and cross-reference them.
Tara: The reality is today with generative AI it is possible, not just with well-structured, but in some cases not particularly well-structured data sets to create those connections, draw out insights that were really not very economical to do, that were so labor intensive. And so now you can have businesses that have multiple distinct data sets. Use generative AI, you get a query tool that is really quite easy to knock together. If you look up a specific topic, it will easily and effectively surface all the data from all the relevant content libraries for you. And that's sort of scratching the surface. But the value to the customer has expanded hugely. Even if they were historically paying for access to all those data sets, they weren't very easy to find. It wasn't obvious, and it couldn't, you know, if you didn't know what you were asking, you were going to hit a dead-end. So actually, it's just helping you be smarter with the query and surface data that already exists. And, as I say, that's kind of entry level. That's table stakes, or it's becoming table stakes. Then you get into if you're creating forecasts, creating a tool that allows people to go in and manipulate those forecasts, so you can rely on someone’s sort of base case scenario but then you can tweak your own inputs.
Tara: And again, you can use generative AI to create some pretty cool products in a cost-effective way. It was always possible to do these things, it's just the bang wasn't really worth the buck. Or interrogate historical data sets where, historically, if you were a customer, you might have needed 25 data scientists to go and really get value out of someone's data sets. Well, actually, you can create tools that help people leverage some of those insights in a much more effective way. So, I think that's where we are right now, and people have varying degrees of success. But it's definitely the next 10 years, I think, are definitely going to be, that's going to be the main place we will see, given that the efficiencies will be quicker to come by.
Tara: I think the third horizon is does generative AI change the game? The existential threat of generative AI, which is a pretty interesting one in the data land. And I'd go back to thinking about what drives value in this sector in the first place. The foundations of these businesses are proprietary data. Even if there's publicly available data points in the data, there's huge value in the consistency, the taxonomy, the linkages, the methodology, the interdependencies of these data series and forecasts. And layered on top of that is all of the enrichment. The so what? Why is this important? The best businesses or the most successful businesses in this sector are valued for their credibility. You call that bankability, call that benchmark status, their entrenchment in a market where most market participants are relying on this single and consistent view as a base case to inform decisions doesn't mean they're doing what it says, but they're saying, okay, this is a pretty good understanding of what's going on now or in the future. We're going to make our own decisions based off this. And in a world where there is more data generated than one person could ever possibly consume, you have to have a starting point to rely on.
Tara: So, I think AI, really, it's the mechanics of helping you do things faster and more effectively. It can help you build a workflow tool, help you embed to customer workflows. But it can't replace credibility, thought leadership, market adoption, the idea of being a data currency. So, we should always be vigilant of the potential of new technologies, but I think it is a massive opportunity. If you can ensure the sanctity of your data and your IP, you don't want other people getting their hands on it, because then they would be able to create the products. But if you've invested over many decades on these historical data sets, or these methodologies that allow you to think of forecast data series. That's where the value is, keep that safe. And then other people will never be able to create the same insights, with the same credibility that you can.
Hiten: It's a really nice way of framing it. Really nice way of framing it. Few images pop up in my head, hearing you talk. I guess there is this protect the crown jewels or this thing at the nucleus at the heart of it, right? Which is ultimately the integrity of that data asset. I think when you were describing the waves, for me, the challenge in wave two was always, oh, can we get more efficient at the data management. However, it's absolutely critical that the data points are right or is right to the best of our knowledge. And that kind of, particularly is the value of the decisions that are made on them go higher and higher. That downside risk of your, I've got really efficiently created data set, but I've traded on the, you know, one percentage of accuracy is traded down that suddenly kind of cause a huge undermining of the value proposition. I think that's always, for me, that's the knotty bit to kind of work through on how far to push things and where things can get to.
Tara: I couldn't agree more. I think, structurally though, even for the past 2 decades, we've seen businesses in this space, as I say, operate 50% margin, some of them. Meaning you don't have to be doing this, we are not in certain markets where you are operating on wafer-thin margins. This is about getting efficiency, not for the sake of efficiency, but where it makes sense. And I think there is a very, very fine balance here, because, as I say, the credibility piece is the piece that is really hard fought, hard won, but very easily lost.
Hiten: There's a Stereophonics song about how a forest can build a thousand matches, but only one match can burn a thousand trees. I age myself. Moving on. Listeners do like to benefit from hearing reflections on people's career journeys, particularly those earlier on at the outset. I'd love to hear from you a reflection on one of your most interesting challenges that you faced on this journey, that you think, you know, others would benefit from hearing about.
Tara: I think I said that those early days were brutal. Actually, just putting one foot in front of the other and getting stuck in and thinking there's a reason just to kind of suck this up and do it for a bit and learn. But I think there's lots of different professional challenges. For me the most enduring challenge actually is the juggling act, right? How do you be the best investor, advisor, leader, colleague, partner, mother, daughter. How do you be what you want to be in all of those things, with so many different relationships, so many different versions of yourself, with huge demands on your time. So learning how to prioritize, to delegate, to recognize when things aren't quite going right and ask for help professionally or personally, that's actually the most interesting challenge that is, as they say, enduring and ever present for me.
Hiten: Say more. I think there's a lot in there, What else would you reflect on as you've gone through that? What do you feel like you're doing now that you didn't do 10, 15 years ago, which you would have loved someone who was, you know, 10, 15 years your seniors sit down, say, hey, Tara, actually, do you know what, how about trying X and Y?
Tara: It depends who you are. I'm a pretty driven results focused person, and probably one of the best advice that I got was to be a bit kinder to myself. You can't do everything all at once. You can't. Some things take time, they take reps. There's a point in your career where you're like, I’ve just got to make, I’ve just got to make it. And you know, we see it typically at sort of that principal level or a VP director at an investment bank and the job changes materially. You change from being rewarded and being valued for just getting it done, right, to figuring out learning how to do it and getting it done. And then you have to evolve a lot into, okay, well, now, it's my call. There's lots of different demands on my time. So actually, you know, be a bit kind to yourself. It does take longer than you think. And that's okay, because actually, it is, without sounding horribly cliched, about the journey, as well as the destination. You learn so much in that journey. And then, as I said, asking for help, prioritizing. Ask for help, like, what am I going to do, what am I not going to do, and clearly communicating. They're to me the biggest things.
Hiten: A lot in there. Thank you for sharing, that's super helpful. As we wrap up, we always invite guests to throw the spotlight, so share or call out an individual or a company that's impressing you right now that you'd want listeners to look up and pay attention to.
Tara: Very far removed from what we've been talking about. But I have a real interest. A lot of the reason I did EHS [Environment, Health and Safety] , ESG, software data and analytics is because I really, I'm interested in that space, particularly around sustainability. And this company, I think, is impressing me and unnerving me all at the same time, it's called Colossal Biosciences, and it's based out of Dallas, Texas. A mere mortal articulation of what they're doing is they're on a mission to recreate a genome sequencing process that can unlock, i.e. birth, extinct or recently extinct species. So, the Tasmanian tiger, the dodo, or critically endangered populations, like the Sumatran tiger or the white rhino. And that in itself is full Jurassic Park, right, slightly terrifying, but slightly awesome. However, the implications of what they might be able to do for human longevity is the bit that's really very cool, like, could they potentially use that genome sequencing to regrow organs? So, there it is, I will never do that business justice, but if you haven't heard of it, I would definitely spend 5 minutes taking a look.
Hiten: I was, just as you were describing it. I was just checking the cup of water, and my table wasn't starting to vibrate.
Tara: Velociraptor at the door.
Hiten: Exactly. Tara, thank you for being so generous for your time and thoughts and coming on the show. It's been really refreshing to hear about your reflections on the journey and your in-depth views on the data space in particular. So, thank you for coming on.
Tara: It's my pleasure. Thank you for having me.
